RAMPVIS: Towards a New Methodology for Developing Visualisation Capabilities for Large-scale Emergency Responses

The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.

[1]  Kai Lawonn,et al.  A Survey of Visual Analytics for Public Health , 2019, Comput. Graph. Forum.

[2]  S. Weghorst,et al.  Emergency Response Planning and Training through Interactive Simulation and Visualization with Decision Support , 2008, 2008 IEEE Conference on Technologies for Homeland Security.

[3]  Hadley Wickham,et al.  Visualizing Complex Data With Embedded Plots , 2015 .

[4]  Dianne Cook,et al.  Glyph‐maps for visually exploring temporal patterns in climate data and models , 2012 .

[5]  Gary K. L. Tam,et al.  Visualization of Time‐Series Data in Parameter Space for Understanding Facial Dynamics , 2011, Comput. Graph. Forum.

[6]  Jeffrey Heer,et al.  SpanningAspectRatioBank Easing FunctionS ArrayIn ColorIn Date Interpolator MatrixInterpola NumObjecPointI Rectang ISchedu Parallel Pause Scheduler Sequen Transition Transitioner Transiti Tween Co DelimGraphMLCon IData JSONCon DataField DataSc Dat DataSource Data DataUtil DirtySprite LineS RectSprite , 2011 .

[7]  Daniel Archambault,et al.  Event-Based Dynamic Graph Visualisation , 2020, IEEE Transactions on Visualization and Computer Graphics.

[8]  Luca Chittaro,et al.  VU-Flow: A Visualization Tool for Analyzing Navigation in Virtual Environments , 2006, IEEE Transactions on Visualization and Computer Graphics.

[9]  Tamara Munzner,et al.  Bridging from Goals to Tasks with Design Study Analysis Reports , 2018, IEEE Transactions on Visualization and Computer Graphics.

[10]  David S. Ebert,et al.  A pandemic influenza modeling and visualization tool☆ , 2011, Journal of Visual Languages & Computing.

[11]  A. Sussman,et al.  Visualization and Communication Tool for Emergency Response , 2018, 2018 IEEE International Symposium on Technologies for Homeland Security (HST).

[12]  Anne E. Trefethen,et al.  Rule‐based Visual Mappings – with a Case Study on Poetry Visualization , 2013, Comput. Graph. Forum.

[13]  Jason Dykes,et al.  Moving beyond sequential design: Reflections on a rich multi-channel approach to data visualization , 2014, IEEE Transactions on Visualization and Computer Graphics.

[14]  Kristin A. Wortman,et al.  Visualization of a Spacecraft Mission Software System , 2015, 2015 IEEE Aerospace Conference.

[15]  Philippe Pinheiro,et al.  Using a Multi-Level and Multi-Resolution Visual Analytics Software to Understand the Aftermath of a Catastrophe , 2019, 2019 IEEE Conference on Visual Analytics Science and Technology (VAST).

[16]  Daniel J. Wigdor,et al.  PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models , 2018, IEEE Transactions on Visualization and Computer Graphics.

[17]  Yifan Hu,et al.  GMap: Drawing Graphs as Maps , 2009, GD.

[18]  Ross T. Whitaker,et al.  Curve Boxplot: Generalization of Boxplot for Ensembles of Curves , 2014, IEEE Transactions on Visualization and Computer Graphics.

[19]  Craig Larman,et al.  Agile and Iterative Development: A Manager's Guide , 2003 .

[20]  K. Bhaskaran,et al.  Time series regression studies in environmental epidemiology , 2013, International journal of epidemiology.

[21]  David Borland,et al.  Data-Driven Healthcare: Challenges and Opportunities for Interactive Visualization , 2016, IEEE Computer Graphics and Applications.

[22]  Juan Carlos Augusto,et al.  Temporal reasoning for decision support in medicine , 2005, Artif. Intell. Medicine.

[23]  Ben Shneiderman,et al.  Interactive Information Visualization to Explore and Query Electronic Health Records , 2013, Found. Trends Hum. Comput. Interact..

[24]  Aidan Slingsby,et al.  Tilemaps for Summarising Multivariate Geographical Variation , 2018 .

[25]  Xiao Zhang,et al.  SensePlace2: GeoTwitter analytics support for situational awareness , 2011, 2011 IEEE Conference on Visual Analytics Science and Technology (VAST).

[26]  Daniel A. Keim,et al.  RescueMark: Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations: Award for Skillful Integration of Language Model , 2019, 2019 IEEE Conference on Visual Analytics Science and Technology (VAST).

[27]  Jimeng Sun,et al.  RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records , 2018, IEEE Transactions on Visualization and Computer Graphics.

[28]  Jürgen Bernard,et al.  A visual active learning system for the assessment of patient well-being in prostate cancer research , 2015, VAHC '15.

[29]  Zhiyuan Zhang,et al.  AnamneVis: A Framework for the Visualization of Patient History and Medical Diagnostics Chains , 2011 .

[30]  Tommy Dang,et al.  EQSA: Earthquake Situational Analytics from Social Media , 2019, 2019 IEEE Conference on Visual Analytics Science and Technology (VAST).

[31]  J. Norris,et al.  Stage: Controlling space robots from a CAVE on Earth , 2012, 2012 IEEE Aerospace Conference.

[32]  Thomas Ertl,et al.  Can Twitter Save Lives? A Broad-Scale Study on Visual Social Media Analytics for Public Safety , 2016, IEEE Transactions on Visualization and Computer Graphics.

[33]  Min Chen,et al.  Categorical Colormap Optimization with Visualization Case Studies , 2017, IEEE Transactions on Visualization and Computer Graphics.

[34]  Eduard Gröller,et al.  Run Watchers: Automatic Simulation-Based Decision Support in Flood Management , 2014, IEEE Transactions on Visualization and Computer Graphics.

[35]  Mei-Po Kwan,et al.  Emergency response after 9/11: the potential of real-time 3D GIS for quick emergency response in micro-spatial environments , 2005, Comput. Environ. Urban Syst..

[36]  Tamara Munzner,et al.  A Nested Model for Visualization Design and Validation , 2009, IEEE Transactions on Visualization and Computer Graphics.

[37]  Jeffrey Heer,et al.  D³ Data-Driven Documents , 2011, IEEE Transactions on Visualization and Computer Graphics.

[38]  Vaninha Vieira,et al.  Information visualization for emergency management: A systematic mapping study , 2016, Expert Syst. Appl..

[39]  Roy A. Ruddle,et al.  QualDash: Adaptable Generation of Visualisation Dashboards for Healthcare Quality Improvement , 2020, IEEE Transactions on Visualization and Computer Graphics.

[40]  Jason Dykes,et al.  Design Exposition Discussion Documents for Rich Design Discourse in Applied Visualization , 2020, IEEE Transactions on Visualization and Computer Graphics.

[41]  Ben Shneiderman,et al.  Temporal Event Sequence Simplification , 2013, IEEE Transactions on Visualization and Computer Graphics.

[42]  David Gotz,et al.  DecisionFlow: Visual Analytics for High-Dimensional Temporal Event Sequence Data , 2014, IEEE Transactions on Visualization and Computer Graphics.

[43]  Aura Ganz,et al.  Distributed visual analytics for collaborative emergency response management , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[44]  Eduard Gröller,et al.  Nodes on Ropes: A Comprehensive Data and Control Flow for Steering Ensemble Simulations , 2011, IEEE Transactions on Visualization and Computer Graphics.

[45]  Tamara Munzner,et al.  Design Study Methodology: Reflections from the Trenches and the Stacks , 2012, IEEE Transactions on Visualization and Computer Graphics.

[46]  David S. Ebert,et al.  An Ontological Framework for Supporting the Design and Evaluation of Visual Analytics Systems , 2019, Comput. Graph. Forum.

[47]  Jonathan C. Roberts,et al.  Sketching Designs Using the Five Design-Sheet Methodology , 2016, IEEE Transactions on Visualization and Computer Graphics.

[48]  Kristina Chodorow,et al.  MongoDB - The Definitive Guide: Powerful and Scalable Data Storage , 2019 .

[49]  Heidrun Schumann,et al.  Visualization of Time-Oriented Data , 2011, Human-Computer Interaction Series.

[50]  Ben Shneiderman,et al.  LifeFlow: visualizing an overview of event sequences , 2011, CHI.

[51]  Min Chen,et al.  What May Visualization Processes Optimize? , 2015, IEEE Transactions on Visualization and Computer Graphics.

[52]  Fred P. Brooks,et al.  The Mythical Man-Month , 1975, Reliable Software.

[53]  Nicole Sultanum,et al.  Doccurate: A Curation-Based Approach for Clinical Text Visualization , 2019, IEEE Transactions on Visualization and Computer Graphics.

[54]  Miriah D. Meyer,et al.  Extending Recommendations for Creative Visualization-Opportunities Workshops , 2020, 2020 IEEE Workshop on Evaluation and Beyond - Methodological Approaches to Visualization (BELIV).

[55]  Stefano Tarantola,et al.  Contribution to the sample mean plot for graphical and numerical sensitivity analysis , 2009, Reliab. Eng. Syst. Saf..

[56]  Daniel J. Wigdor,et al.  PhenoStacks: Cross-Sectional Cohort Phenotype Comparison Visualizations , 2017, IEEE Transactions on Visualization and Computer Graphics.

[57]  Jason Dykes,et al.  Action Design Research and Visualization Design , 2016, BELIV '16.

[58]  Michelle A. Borkin,et al.  Design Study "Lite" Methodology: Expediting Design Studies and Enabling the Synergy of Visualization Pedagogy and Social Good , 2020, CHI.

[59]  Hongyuan Zha,et al.  Visual Progression Analysis of Event Sequence Data , 2019, IEEE Transactions on Visualization and Computer Graphics.

[60]  Denis Gracanin,et al.  Interactive Visual Analysis of Families of Function Graphs , 2006, IEEE Transactions on Visualization and Computer Graphics.

[61]  M. Sheelagh T. Carpendale,et al.  Distributed Synchronous Visualization Design: Challenges and Strategies , 2020, ArXiv.

[62]  Kyle Wm. Hall,et al.  Design by Immersion: A Transdisciplinary Approach to Problem-Driven Visualizations , 2019, IEEE Transactions on Visualization and Computer Graphics.

[63]  Jonathan C. Roberts,et al.  A coordination model for exploratory multiview visualization , 2003, Proceedings International Conference on Coordinated and Multiple Views in Exploratory Visualization - CMV 2003 -.

[64]  Alfred Inselberg,et al.  Parallel coordinates: a tool for visualizing multi-dimensional geometry , 1990, Proceedings of the First IEEE Conference on Visualization: Visualization `90.

[65]  Jason Dykes,et al.  Human-Centered Approaches in Geovisualization Design: Investigating Multiple Methods Through a Long-Term Case Study , 2011, IEEE Transactions on Visualization and Computer Graphics.

[66]  Sara Jones,et al.  A Framework for Creative Visualization-Opportunities Workshops , 2018, IEEE Transactions on Visualization and Computer Graphics.

[67]  Stephen G. Kobourov,et al.  Drawing Dynamic Graphs Without Timeslices , 2017, GD.

[68]  Harry Hochheiser,et al.  NLPReViz: an interactive tool for natural language processing on clinical text , 2018, J. Am. Medical Informatics Assoc..

[69]  Sara Jones,et al.  Creative User-Centered Visualization Design for Energy Analysts and Modelers , 2013, IEEE Transactions on Visualization and Computer Graphics.

[70]  Jari Saramäki,et al.  Temporal Networks , 2011, Encyclopedia of Social Network Analysis and Mining.

[71]  Usman Alim,et al.  UofC-Bayes: A Bayesian Approach to Visualizing Uncertainty in Radiation Data , 2019, 2019 IEEE Conference on Visual Analytics Science and Technology (VAST).

[72]  Torsten Möller,et al.  Sliceplorer: 1D slices for multi‐dimensional continuous functions , 2017, Comput. Graph. Forum.

[73]  Landon Fridman Detwiler,et al.  Visualization and analytics tools for infectious disease epidemiology: A systematic review , 2014, J. Biomed. Informatics.

[74]  Keke Wu,et al.  Designing for Mobile and Immersive Visual Analytics in the Field , 2019, IEEE Transactions on Visualization and Computer Graphics.

[75]  Robert S. Laramee,et al.  Survey of Surveys (SoS) ‐ Mapping The Landscape of Survey Papers in Information Visualization , 2017, Comput. Graph. Forum.

[76]  Ross T. Whitaker,et al.  Contour Boxplots: A Method for Characterizing Uncertainty in Feature Sets from Simulation Ensembles , 2013, IEEE Transactions on Visualization and Computer Graphics.

[77]  Eduard Gröller,et al.  Sketching Uncertainty into Simulations , 2012, IEEE Transactions on Visualization and Computer Graphics.

[78]  Katharine T. Adams,et al.  Rapid development of visualization dashboards to enhance situation awareness of COVID-19 telehealth initiatives at a multihospital healthcare system , 2020, J. Am. Medical Informatics Assoc..